An ant colony aggregation cell tracking system based on potential estimation

Abstract

The invention discloses an ant colony aggregation cell tracking system assisted by potential estimation, which realizes the tracking of aggregated cells through the analysis of cell potential prediction and initial distribution module of pheromone field, ant search rule module, pheromone field existence probability update module and cell potential estimation and state extraction module. After theoriginal image is input, the cell potential is predicted by the existence probability of the pheromone field. The pheromone field is constructed by using a pheromone diffusion model based on a conicalcurve in an ant search mode based on pheromone gradient exponential form. On the basis, the existence probability of pheromone field is updated and the cell potential and state are estimated at the same time. Finally, the cell motion trajectory is obtained by using the distance relationship between cells, and the tracking of aggregated cells is realized. The invention can accurately estimate thenumber and the state of the aggregated cells, and has good tracking effect on the multicellular tracking of the cells entering or leaving the view.

Description

technical field [0001] The invention belongs to the field of cell tracking, and more particularly relates to an ant colony aggregation cell tracking system based on potential estimation assistance. Background technique [0002] Cell characteristics are the basic information reflecting the state of life. With the development of microscope imaging technology and biomedical image technology, the research of cell movement is widely used in medical diagnosis, disease treatment and drug development. Relying on digital image processing technology to solve problems including cell staining, counting, classification and tracking can free researchers from heavy and repetitive labor, and as a non-contact and non-invasive automatic measurement method, it can be more effective Reflect the natural growth state and behavior of cells. Therefore, more and more researchers pay attention to multi-cell automatic tracking technology based on microscopic images. [0003] Cell tracking or motion...

AI Technical Summary

Problems solved by technology

[0006] In terms of cell tracking, some achievements have been made in recent years, but most of them rely on accurate cell detection information. For complex and diverse cell image sequences, the tracking accuracy is not high, and it is difficult to accurately describe its statistical properties.

At present, due to the different research purposes of most scholars, the relationship between the research results related to cell tracking is relatively loose, and there is a lack of a unified and perfect cell tracking system and framework.

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